The transcriptome of circulating cells indicates potential biomarkers and therapeutic targets in the course of hypertension-related myocardial infarction

Figure 1. The volcano plot of the microarray mRNA or miRNA expression in GEO datasets. (A) The volcano plot of mRNA profile GSE-HT (GSE24752). (B–D) The volcano plot of mRNA profile GSE-MI (GSE60993 and GSE62646 separately and combined data of GSE60993 and GSE62646 after batch correction). (E) The volcano plot of miRNA profile mi-GSE-MI (GSE24548). Orange: higher expression, blue: lower expression.

Figure 2. Hierarchical clustering analysis of DEGs. (A–C) Results of hierarchical clustering analysis of expression of HT-DEGs in relation to immune responses, cellular signaling, and T-cell activation. (D–F) Results from hierarchical clustering analysis of expression of MI-DEGs in relation to immune responses, cellular signaling, and an inflammatory response. Orange: higher expression, blue: lower expression.

Figure 3. PPI network and Venn diagrams: (A-B) PPI networks according to the STRING database for HT-DEGs and MI-DEGs, respectively (threshold > 0.4). (C) Venn diagrams of co-DEGs specific to HT-related MI. Two co-DEGs, FOLR3 and NFE2, were identified. (D–G) PPI networks according to the STRING database for the module including FOLR3 and NFE2 among HT-DEG and MI-DEGs, respectively (threshold > 0.4). Nodes: proteins, interactions (edges): lines between DEGs.

Figure 4. Dot plots of enrichment in GO terms and KEGG pathways: (A and D) GO term enrichment of the HT-related DEG set and MI-related DEG set, respectively. (B and E) KEGG pathway enrichment of the HT- and MI-related DEG sets, respectively. (C and F) Functional and pathway enrichment according to the Reactome database for the HT- and MI-related DEG sets, respectively. Dot sizes represent counts of enriched DEGs, and dot colors represent negative log10P values. Red: higher expression, blue: lower expression.

Figure 5. GSEA of expression of co-DEGs in patients with MI. (A) Expression profiling data were divided into datasets “NFE2 lower expression” and “NFE2 higher expression” according to the median NFE2 expression level. (B) Expression profiling data were divided into datasets “FOLR3 lower expression” and “FOLR3 higher expression” according to the median FOLR3 expression level in the batch-corrected MI dataset (combined datasets GSE60993 and GSE62646). Visualization was implemented in GSEA 3.0 software. The final map was generated by means of R packages “plyr,” “ggplot2,” “grid,” and “gridExtra” for removal of any general or noninformative smaller networks to simplify the final diagram.

Figure 6. Relations with various diseases in general, metabolic diseases in particular, and CVDs related to the co-DEGs according to the Comparative Toxicogenomics Database. (A-B) Results from the Comparative Toxicogenomics Database on NFE2. (C-D) Results from the Comparative Toxicogenomics Database on FOLR3.

Figure 7. Hierarchical clustering analysis of DE-miRNAs. (A) Results of hierarchical clustering analysis of expression of MI-specific DE-miRNAs. (B-C) Microarray expression levels of miR-7 and miR-538 in GSE24548 in detailed representation. Orange: higher expression, blue: lower expression.